Application of multi-source remote sensing data in the exploration of sandstone-type uranium deposits: A case study of the Yingen area, Bayingebi basin

Sandstone-type uranium deposits emerge as important uranium resources, while remote sensing is identified as a vital method for mineral resource exploration. Since sandstone-type uranium deposits typically occur underground and tend to be covered by sediments, whether remote sensing can be effectively applied to the exploration of such deposits merits investigation. This study investigated the Yingen area in the Bayingobi basin. Utilizing multi-source remote sensing data from Sentinel2, Landsat7 ETM+, ASTER, ALOS DEM, and airborne radioactivity measurements, this study performed terrain visualization, structural interpretations, K-T transformation, NDVI index calculation, alteration mineral extraction, and Th/U ratio calculation. The results were then comprehensively analyzed from the perspective of the metallogenic model, metallogenic conditions, and ore-controlling factors of secondary reduced sandstone-type uranium deposits. The analytical results indicate that the Yingen area consists of an uplift zone in the center, a depression zone in the southeast, and a slope zone between them. The granitic rocks in the uplift zone are identified as significant sources of uranium. Multiple EW-trending faults in the slope zone facilitate the migration of uranium-bearing oxidized water underground. Additionally, the water-rich areas in the depression zone, combined with strong surface evaporation, create favorable conditions for the drainage and evaporation of uranium-bearing oxidized water, further promoting groundwater circulation. Therefore, the uplift zone, slope zone, and depression zone in the Yingen area form a complete circulation system for uranium-bearing oxidized water. In combination with previous data, this study holds that the slope zone might serve as a favorable area for the formation of secondary reduced sandstone-type uranium deposits. This study also demonstrates that even in seriously overburden areas, remote sensing can provide valuable guidance for uranium exploration by identifying metallogenic conditions and ore-controlling factors.